MassIVE MSV000084048

Partial Public PXD015303

Epithelial ovarian cancer biomarker

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Description

Protein biomarkers of early stages of disease are critical for managing the disease and improving outcomes. Unfortunately, discovery of protein biomarkers is hampered by the limited availability of assays for sensitive and reproducible quantification of proteins in complex biological matrices such as blood plasma. In the recent years, Selected Reaction Monitoring (SRM) has emerged as a robust mass spectrometric method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing protein biomarkers for epithelial ovarian cancer, and illustrate the extent to which SRM platform, combined with sound experimental design and statistical analysis, results in robust detection of predictive analytes. First, the biomarker development was guided by a discovery-driven proteomic effort to detect potential N-glycoprotein biomarker candidates in tissue of a genetically stable ovarian cancer mouse model. Next, 65 candidate markers were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive 5-protein signatures for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion. [doi:10.25345/C5PW7B] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: SRM ; Biomarker ; Ovarian cancer ; MassIVE.quant reviewed - Platinum

Contact

Principal Investigators:
(in alphabetical order) 		Meena Choi, Northeastern University, United States
Ruth Huttenhain, Department of Molecular and Cellular Pharmacology, UCSF, USA
Submitting User: mnchoi

Publications

Hüttenhain R, Choi M, Martin de la Fuente L, Oehl K, Chang CV, Zimmermann AK, Malander S, Olsson H, Surinova S, Clough T, Heinzelmann-Schwarz V, Wild PJ, Dinulescu DM, Niméus E, Vitek O, Aebersold R.
A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer.
Mol. Cell Proteomics. 2019 Sep;18(9):1836-1850. Epub 2019 Jul 9.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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